Chemoinformatic Exploration of "Bioinspired Metabolomes" Illuminates Diacetyl Assembly Pathways Toward Nesteretal A-Like Cage Molecules.

An appealing and challenging cage structure along with an unusual biosynthetic pathway prompted us to explore an expeditious bioinspired one-pot total synthesis of nesteretal A. An unconventional strategy was chosen, and a cascade reaction starting from diacetyl was studied. Under organocatalytic conditions mimicking an aldolase, nesteretal A and a related cage analogue were anticipated by in silico metabolization, detected, targeted, and characterized.

HyPyP: a Hyperscanning Python Pipeline for inter-brain connectivity analysis.

The bulk of social neuroscience takes a 'stimulus-brain' approach, typically comparing brain responses to different types of social stimuli, but most of the time in the absence of direct social interaction. Over the last two decades, a growing number of researchers have adopted a 'brain-to-brain' approach, exploring similarities between brain patterns across participants as a novel way to gain insight into the social brain. This methodological shift has facilitated the introduction of naturalistic social stimuli into the study design (e.g. movies) and, crucially, has spurred the development of new tools to directly study social interaction, both in controlled experimental settings and in more ecologically valid environments. Specifically, 'hyperscanning' setups, which allow the simultaneous recording of brain activity from two or more individuals during social tasks, has gained popularity in recent years. However, currently, there is no agreed-upon approach to carry out such 'inter-brain connectivity analysis', resulting in a scattered landscape of analysis techniques. To accommodate a growing demand to standardize analysis approaches in this fast-growing research field, we have developed Hyperscanning Python Pipeline, a comprehensive and easy open-source software package that allows (social) neuroscientists to carry-out and to interpret inter-brain connectivity analyses.

Interactive Psychometrics for Autism With the Human Dynamic Clamp: Interpersonal Synchrony From Sensorimotor to Sociocognitive Domains.

The human dynamic clamp (HDC) is a human-machine interface designed on the basis of coordination dynamics for studying realistic social interaction under controlled and reproducible conditions. Here, we propose to probe the validity of the HDC as a psychometric instrument for quantifying social abilities in children with autism spectrum disorder (ASD) and neurotypical development. To study interpersonal synchrony with the HDC, we derived five standardized scores following a gradient from sensorimotor and motor to higher sociocognitive skills in a sample of 155 individuals (113 participants with ASD, 42 typically developing participants; aged 5 to 25 years; IQ > 70). Regression analyses were performed using normative modeling on global scores according to four subconditions (HDC behavior "cooperative/competitive," human task "in-phase/anti-phase," diagnosis, and age at inclusion). Children with ASD had lower scores than controls for motor skills. HDC motor coordination scores were the best candidates for stratification and diagnostic biomarkers according to exploratory analyses of hierarchical clustering and multivariate classification. Independently of phenotype, sociocognitive skills increased with developmental age while being affected by the ongoing task and HDC behavior. Weaker performance in ASD for motor skills suggests the convergent validity of the HDC for evaluating social interaction. Results provided additional evidence of a relationship between sensorimotor and sociocognitive skills. HDC may also be used as a marker of maturation of sociocognitive skills during real-time social interaction. Through its standardized and objective evaluation, the HDC not only represents a valid paradigm for the study of interpersonal synchrony but also offers a promising, clinically relevant psychometric instrument for the evaluation and stratification of sociomotor dysfunctions.

MetWork: a web server for natural products anticipation.

MOTIVATION: The annotation of natural products and more generally small molecules is one of the major drawbacks in untargeted mass spectrometry analysis. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments. Despite the great potential of this tool, the annotation is usually performed manually by the expert as only few spectral libraries are available. RESULTS: Herein we propose a web server of in silico metabolization of metabolites that represents a full implementation of the metabolome consistency concept. The workflow is based on MS/MS data, organized in molecular network using the Global Natural Products Social Molecular Networking (GNPS) platform, a collaborative library of reactions and a MS/MS spectra prediction module. Having one node identified in the molecular network, the server generates putative structures and predict the associated MS/MS spectra when the exact mass is detected in the network. A similarity comparison between the MS/MS spectra is then performed in order to annotate the node. AVAILABILITY AND IMPLEMENTATION: The web server is available at: https://metwork.pharmacie.parisdescartes.fr.